Graduate Research Assistant | MS Applied Data Science @ Syracuse University
I build end-to-end machine learning systems, deploy AI applications, and translate complex data into decisions that matter. My work spans deep learning for space weather forecasting, NLP explainability for financial models, LLM-powered data pipelines, and predictive analytics for agricultural and political systems.
Currently working as a Graduate Research Assistant at Syracuse University's Lender Centre for Social Justice, where I build interactive geospatial dashboards and analyze housing policy data for government stakeholders and community organizations.
Previously worked as a Power BI Developer at Senwell Group, building end-to-end operational data applications using Power Apps, Power Automate, and Snowflake. Before that, as a Data Scientist at ChemView Consulting, I automated consulting report generation reducing manual effort from 3+ hours to under 30 minutes.
I am currently pursuing coursework in Financial Analytics and Advanced Big Data Management.
| Project | Description | Stack | Demo |
|---|---|---|---|
| FinBERT LLM Explainability | Comparing SHAP vs LIME on FinBERT for financial sentiment analysis on 9,543 tweets | Python, HuggingFace, SHAP, LIME | Live Demo |
| Aurora Geomagnetic Forecasting | LSTM neural network for space weather prediction with 48% RMSE improvement over baseline across 1, 3, 6, 12 hour horizons | Python, TensorFlow, Keras, NASA OMNI2 | |
| Text to SQL with LangChain | Query a relational database using plain English via LangChain and Llama 3.3 70B | Python, LangChain, Groq, SQLite | |
| Democratic Values & Political Ideology Analysis | Cross-national analysis of populism's impact on democratic values across six countries using V-Dem dataset (1970 to 2020) | R, rstanarm, Bayesian Analysis, ggplot2 | |
| Agricultural Yield Prediction | Gradient Boosted Decision Tree model predicting pollution's impact on rice crop yields across Indian districts (13,215 records) | R, Shiny, Gradient Boosting, XGBoost | |
| Energy Demand Forecasting | Predicting residential energy demand for July using Random Forest and XGBoost in R. R² = 0.478 | R, Shiny, Random Forest, XGBoost | Live App |
Languages: Python, R, SQL (MySQL)
Machine Learning: Random Forest, Gradient Boosting, XGBoost, Linear/Logistic Regression, Ridge, Lasso, K-Means Clustering, Feature Engineering, Hyperparameter Tuning
Deep Learning: LSTM, CNN, RNN, TensorFlow, Keras, Model Evaluation
NLP & LLMs: FinBERT, LangChain, SHAP, LIME, HuggingFace, Groq API, OpenAI API
Statistical Methods: Hypothesis Testing, Bayesian Analysis (rstanarm, stan_glm), Time Series Analysis, Regression Analysis, ANOVA
BI & Visualization: Power BI (DAX), Tableau, Looker Studio, ArcGIS Online, ArcGIS Experience Builder, ggplot2, Matplotlib, Seaborn
Cloud & Databases: AWS (Cloud Practitioner Certified), Snowflake, MySQL, SQLite
Automation & Development: Power Apps, Power Automate, Streamlit, GitHub
Libraries: Pandas, NumPy, Scikit-learn, XGBoost, Statsmodels
Graduate Research Assistant | Lender Centre for Social Justice, Syracuse University (Aug 2025 to Present)
- Built 5+ ArcGIS dashboards translating census and socioeconomic data into accessible visualizations for policymakers
- Analyzed housing crisis data and drafted policy recommendations for government stakeholder discussions
- Standardized 10+ census datasets reducing 30+ columns to 10 key indicators per domain
Power BI Developer | Senwell Group Pvt. Ltd (Apr 2024 to Jul 2024)
- Built end-to-end operational data application using Power Apps, Power Automate, and Power BI with Snowflake integration
- Developed 8+ interactive dashboards enabling stakeholders to filter and drill down through operational data
Data Scientist | ChemView Consulting Pvt. Ltd (Nov 2023 to Mar 2024)
- Reduced manual consulting report generation time from 3+ hours to under 30 minutes via Streamlit automation
- Analyzed 80+ page industry reports across 7 regions to identify automation opportunities
Data Analyst Intern | Data Science Masterminds, Bangalore (Aug 2023 to Nov 2023)
- Developed performance scorecards and business intelligence dashboards using Power BI, Python, SQL, and Excel
- Conducted data analysis across multiple client projects, delivering actionable insights through statistical methods and visualization
- Graduate Research Assistant at Syracuse University building housing policy dashboards for government stakeholders
- Coursework: Advanced Big Data Management, Financial Analytics, Lean Six Sigma (Green Belt)
- Building Streamlit UI for Text to SQL LangChain project with live deployment
- Developing finance focused projects: stock price prediction, options pricing, portfolio optimization
MS Applied Data Science | Syracuse University (Jan 2025 to Dec 2026) | GPA: 3.61/4.0
Completed: Introduction to Data Science, Database Administration and Management, Quantitative Reasoning, Applied Machine Learning, Deep Learning, Business Analytics
In Progress: Advanced Big Data Management, Financial Analytics, Lean Six Sigma
BSc Data Science | Symbiosis Skills and Professional University, Pune (Aug 2019 to Aug 2022) | GPA: 3.38/4.0
- AWS Certified Cloud Practitioner (2022)
MS Applied Data Science, Syracuse University | Graduating December 2026 | Open to Summer 2026 Internships